Neural network based dynamic pole placement control of nonlinear systems

2009 ◽  
Author(s):  
Eduard Petlenkov ◽  
Juri Belikov
Keyword(s):  
Neural Network ◽  
Nonlinear Systems ◽  
Pole Placement ◽  
Pole Placement Control

Adaptive Pole Placement Control Algorithm for Nonlinear Systems

1997 ◽  
Vol 05 (02) ◽  
pp. 139-146 ◽  
Author(s):  
Jin Wang ◽  
Wenzhong Gao
Keyword(s):  
Neural Network ◽  
Control Algorithm ◽  
Learning Algorithm ◽  
Recursive Least Squares ◽  
Pole Placement ◽  
Rls Algorithm ◽  
Pole Placement Controller ◽  
Nonlinear Plants ◽  
Adaptive Control Algorithm ◽  
Pole Placement Control

A new adaptive control algorithm for unknown nonlinear plants is presented. The paper first describes a modified neural network(MNN) as well as the associated learning algorithm. The learning algorithm converges considerably faster because of the introduction of recursive least squares(RLS) algorithm. And then designs adaptive pole placement controller based on the modified neural network. Simulation results show that the proposed control algorithm can effectively control nonlinear plants.

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